1. Field of the Invention
The present invention relates to a learning device and method, a recognition device and method, and a program, and specifically, a learning device and method, a recognition device and method, and a program, which enable a target object to be detected from an image in a surer manner.
2. Description of the Related Art
Heretofore, technology for detecting a person from an image has been studied and developed principally for security or in-vehicle use (e.g., see Navneet Dalal and Bill Triggs “Histograms of Oriented Gradients for Human Detection” CVPR2005, and B. Wu and R. Nevatia “Detection of multiple, partially occluded humans in a single image by bayesian combination of edgelet part detectors” In Proc. 10th Int. Conf. Computer Vision, 2005). With Navneet Dalal and Bill Triggs “Histograms of Oriented Gradients for Human Detection” CVPR2005, and B. Wu and R. Nevatia “Detection of multiple, partially occluded humans in a single image by bayesian combination of edgelet part detectors” In Proc. 10th Int. Conf. Computer Vision, 2005, a feature amount to be obtained by edge extraction is employed as a principal feature amount for detecting (recognizing) a person from an image. With these techniques, various variations of a feature amount obtained by edge extraction are defined as a new feature amount, and recognition of a person is performed.
For example, with Navneet Dalal and Bill Triggs “Histograms of Oriented Gradients for Human Detection” CVPR2005, there is provided an advantage wherein a feature amount is obtained by obtaining a histogram in a direction within a small region including an edge, and employing this feature amount makes this technique strong against some distortion of outlines, and so forth.